时间序列论文趋势 2023–2026
预测与异常检测
统计范围:NeurIPS、ICLR、ICML、CVPR 四个会议,2023–2026 年,共 2,157 篇被归入该主题的论文。
主要结论
- 时间序列论文从 2023 年的 272 篇增长到 2026 年的 876 篇,三年间扩大到约 3.2 倍。
- NeurIPS 是发时间序列论文最多的会议,2023–2026 年共 757 篇,占四个会议总量的 35%。
- 交叉方向里涨得最快的是多模态大模型:同时属于两个主题的论文从 2023 年的 6 篇增至 2026 年的 85 篇。
- 在「图与结构化数据」的 5 个主题里,它的 2026 年论文数排第 1;同组增长最快的分子建模是 2.7 倍,时间序列是 3.2 倍。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 91 | 60 | 62 | 59 | 272 |
| 2024 | 147 | 95 | 114 | 68 | 424 |
| 2025 | 221 | 131 | 159 | 74 | 585 |
| 2026 | 298 | 220 | 264 | 94 | 876 |
代表论文
按年份和会议均匀挑选,方便快速看到每一届的样貌
- NeurIPS 2026A Batched Hartigan's $k$-Means Clustering
- ICML 2026A Control-Theoretic View of Mamba on Stability and Robustness
- ICLR 2026A Single Architecture for Representing Invariance Under Any Space Group
- CVPR 2026Activation Matters Test-time Activated Negative Labels for OOD Detection with
- NeurIPS 2025Abstain Mask Retain Core: Time Series Prediction by Adaptive Masking Loss with Representation Consistency
- ICML 2025$K^2$VAE: A Koopman-Kalman Enhanced Variational AutoEncoder for Probabilistic Time Series Forecasting
- ICLR 2025A deep inverse-mapping model for a flapping robotic wing
- CVPR 2025Beyond Single-Modal Boundary: Cross-Modal Anomaly Detection through Visual Prototype and Harmonization
- NeurIPS 2024A Continuous-time Stochastic Gradient Descent Method for Continuous Data
- ICML 2024$S^2$IP-LLM: Semantic Space Informed Prompt Learning with LLM for Time Series Forecasting
- ICLR 2024ARM: Refining Multivariate Forecasting with Adaptive Temporal-Contextual Learning
- CVPR 2024Each Test Image Deserves A Specific Prompt: Continual Test-Time Adaptation for 2D Medical Image Segmentation
- NeurIPS 2023A Sublinear-Time Spectral Clustering Oracle with Improved Preprocessing Time
- ICML 2023Accounting For Informative Sampling When Learning to Forecast Treatment Outcomes Over Time
- ICLR 2023A Time Series is Worth 64 Words: Long-term Forecasting with Transformers
- CVPR 2023ActMAD: Activation Matching To Align Distributions for Test-Time-Training
- NeurIPS 2026A Locally Tokenized Generative Model for Robust Time-Series Watermarking
- ICML 2026ADHD Disease Detection Based on Short- and Long-Term Brain Function Encoding and Memory Graph Network
- ICLR 2026A Spectral-Grassmann Wasserstein metric for operator representations of dynamical systems
- CVPR 2026Continuous Exposure-Time Modeling for Realistic Atmospheric Turbulence Synthesis
全部时间序列论文
共 298 篇,第 3 / 6 页
- NeurIPS 2026FracTS: Hierarchical and Autoregressive Time Series Generation
- NeurIPS 2026From Cortical Synchronous Rhythm to Brain Inspired Learning Mechanism: An Oscillatory Spiking Neural Network with Time-Delayed Coordination
- NeurIPS 2026From Post-Hoc to Ante-Hoc: Consistently Explainable Semi-Supervised Time Series Classification
- NeurIPS 2026Full-Atom Cyclic Peptide Design via Test-Time Scaled Autoregressive Flow Matching
- NeurIPS 2026GAPS: Gradient-Aware Adaptation-Gap Scoring for Time-Series Anomaly Detection with Foundation Models
- NeurIPS 2026Generating Financial Time Series by Matching Random Convolutional Features
- NeurIPS 2026GeoWind2Plan: Mission-Time 3D Urban Wind Prediction for Energy-Efficient UAV Planning
- NeurIPS 2026HARMONY: Hierarchical Anchor Retrieval on Manifold for Oblivious-source Acoustic Anomaly Detection
- NeurIPS 2026Hermes: A Multi-Scale Spatial-Temporal Hypergraph Network for Stock Time Series Forecasting
- NeurIPS 2026High-dimensional Gaussian Graphical Model Testing for Long-Memory Time Series
- NeurIPS 2026History-Aware Conformal Prediction Sets for Censored Time-to-Event Outcomes
- NeurIPS 2026Hitting a Moving Target: Test-Time Adaptation for AI Text Detection under Continual Distribution Shift
- NeurIPS 2026Hitting Time Isomorphism for Multi-Stage Planning with Foundation Policies
- NeurIPS 2026HyFAD: Hybrid Time-Frequency Diffusion with Frequency-Aware Embedding for Time Series Imputation
- NeurIPS 2026Improving Audit Realism with Inference-Time Compute and Deployment Scaffolds
- NeurIPS 2026IMTS-Tokenizer: Time-Aware Tokenization for Irregular Multivariate Time Series Forecasting
- NeurIPS 2026InCLAD: A Continual Learning Benchmark for Industrial Visual Anomaly Detection
- NeurIPS 2026Inference Time Nash Alignment
- NeurIPS 2026Inference-time Alignment via Sparse Junction Steering
- NeurIPS 2026Inference-Time Self-Aligned Drifting for Few-Step Flow Matching
- NeurIPS 2026Internal Evaluation of Unsupervised Anomaly Detection Algorithms with Explanation
- NeurIPS 2026Inverted Detection and Control in Steering Vectors
- NeurIPS 2026JEDI: Real-Time Jailbreak Defense for LLMs via In-Generation Detection and Intervention
- NeurIPS 2026Joint Consistency: A Unified Test-Time Aggregation Framework via Energy Minimization
- NeurIPS 2026Kairos: Toward Adaptive and Parameter-Efficient Time Series Foundation Models
- NeurIPS 2026Koopman Generative Operators for Efficient Probabilistic Time-Series Forecasting
- NeurIPS 2026Layer Precision Reduction for Deep Anomaly Detection
- NeurIPS 2026Learned Lagrangian Models of PDEs via Euler–Lagrange Residual Minimization
- NeurIPS 2026Learning Collision‑Free Dispatch Policies for Route‑Wise Decision‑Dependent Anomaly Detection
- NeurIPS 2026Learning Planning Budgets in Real-Time RL
- NeurIPS 2026Learning to Trigger: Reinforcement Learning at the Large Hadron Collider
- NeurIPS 2026Linear-time rule mining under formal guarantees
- NeurIPS 2026Lipschitz Dueling Bandits over Continuous Action Spaces
- NeurIPS 2026LLMs Improving LLMs: Agentic Discovery for Test-Time Scaling
- NeurIPS 2026LogSig-SSM: Time-Series Modelling with Multi-Scale Log-Signature Compression for State-Space Models
- NeurIPS 2026Mamba Can Learn Low-Dimensional Targets In-Context via Test-Time Feature Learning
- NeurIPS 2026Mamba Flow Matching Neural Processes: Linear-Time Inference for Irregularly Observed Spatial Fields
- NeurIPS 2026Marrying Optimal Transport and ODEs for Unified Continuous-Time 4D Reconstruction and Tracking
- NeurIPS 2026MDK-MoE: Multi-view Decomposed Kalman Mixture of Experts Framework for Non-stationary Time Series Forecasting
- NeurIPS 2026Measure Less, Know More: Self-Supervised Test-Time Feature Acquisition
- NeurIPS 2026Measuring Robustness and Efficiency in a Connectome-Constrained Fly Visual System Model on a Collision-Detection Task
- NeurIPS 2026Membrane Sensitivity and Deployment Fragility of Learnable Time Constants in Spiking Neural Networks
- NeurIPS 2026MissPath-FM: Flow Matching with Structured Priors for Partially Observed Time Series
- NeurIPS 2026MMTA: Benchmarking Multimodal Temporal Analysis with Time Series, Text, and Vision
- NeurIPS 2026Monotone Inclusion Approach to Weakly Monotone Discrete-Time Finite-Horizon Mean-Field Games
- NeurIPS 2026MOSAIC: Module Discovery via Sparse Additive Identifiable Causal Learning for Scientific Time Series
- NeurIPS 2026MSAR: Next-Scale Autoregressive Forecasting for Time Series via Modular Multi-Scale Decoupling
- NeurIPS 2026Multivariate Time Series Forecasting needs Cross Variable Loss
- NeurIPS 2026Near-Linear Time Generalized Sinkhorn Algorithms for Bounded Genus Graphs
- NeurIPS 2026Near-Optimal Regret in Adversarial Kernel Bandits
在 Claude、Cursor 里直接问这个趋势
接上 Paperlist MCP 后,写综述、挑方向或准备投稿时,不用离开对话框就能拿到这页的数字:每年各会议的论文数、增长倍数、涨得最快的子方向和代表论文,AI 会按你的问题整理。
可以直接复制这句话问 AI
用 paperlist 查时间序列在 NeurIPS 2023–2026 的论文趋势,哪一年涨得最快?
AI 会调用的工具:get_topic_stats {"topic": "time-series"}
常见问题
- 2023–2026 年四大会议一共有多少篇时间序列论文?
- 共 2,157 篇,按年份分别是 2023 年 272 篇、2024 年 424 篇、2025 年 585 篇、2026 年 876 篇。
- NeurIPS 2026 有多少篇时间序列论文?
- NeurIPS 2026 有 298 篇时间序列论文,上一届是 221 篇。
- ICLR 2026 有多少篇时间序列论文?
- ICLR 2026 有 220 篇时间序列论文,上一届是 131 篇。
- ICML 2026 有多少篇时间序列论文?
- ICML 2026 有 264 篇时间序列论文,上一届是 159 篇。
- CVPR 2026 有多少篇时间序列论文?
- CVPR 2026 有 94 篇时间序列论文,上一届是 74 篇。
- 哪个会议的时间序列论文最多?
- NeurIPS,2023–2026 年共 757 篇。